Background

It has never been harder to pick a restaurant in New York City. Too often, when we rely upon digital tools to help us decide, we are either inundated with jaded reviews from anonymous strangers, provided recommendations from tastemakers whose opinions and values don't reflect our own, or given impersonal, inaccurate algorithmic distillations of what's "best" for us from sites like Yelp.

What's more, we have never had so many options to choose from. If you just search "Restaurants" for New York City on Yelp, you are given more than 50,000 options. Yet having more options doesn't lead to easier decisions or better meals.

I decided to start digging a little deeper.

As part of my initial research, I asked around 80 friends and family, ITP colleagues and undergraduate friends to give me their go to spot for food in New York - the kind of place you would make sure to go to one last time before moving to a different city - your "Last Eats", if you will. Of those 80 responses, 35 were for New York City.

Only one response matched a single restaurant on Yelp's Top 10 best choices.

What this immediately showed me was that Yelp doesn't actually know us best, food is inherently personal and that the best match from Yelp is nearly no match for us at all. As a result,I wanted to design a product that leverages your trusted network to make deciding where to eat the fastest, easiest and most satisfying experience possible.

The Problem

The Competitive Landscape

As part of my research for my thesis, I did a comprehensive study into the mechanics of Yelp as well as many other leading food discovery apps including: Opentable, Urbanspoon, Foodspotting, Zagat, Ness, Chef's Feed, Forkly and dozens more.

Friends Over Food Finder Apps

There are so many food discovery apps and yet time and time again I would find friends disregarding ALL of these options in favor of asking their buddies on Facebook where to eat.

Choice Paralysis

On Yelp, the average rating is nearly 4 out of 5 stars. To understand this on more granular terms, if you search "Cheap Dinner" in the East Village, only 2% of the venues are given a bad rating (which is less than three stars). The problem this creates is that when everything is special, nothing is and it becomes increasingly difficult to choose.

The instinct of every food discovery app is to put as many dots on a map as possible. "Look at all the options you have! Isn't this great?"

Unfortunately, leading psychologists in the field of choice paralysis beg to differ. Simply put, more and more options for the consumer invariably leads to something known as "The Paradox of Choice" or "Choice Paralysis". Two of the preeminent experts in this domain are Sheena Iyengar (Columbia Business School) and Barry Schwartz (Swarthmore College). Based on a methodology gleaned from their insights, Last Eats takes the opposite approach.

User Research - The Importance of Trust

On top of my research into Choice Paralysis, I wanted to confirm there was a community that valued trust and the intimacy of friends giving friends word of mouth recommendations. So I did a survey of 40 people. I asked them to tell me which they was the most useful and trustworthy way to discover food:

33 of 40 users responded that a friend or relative's recommendation was the most useful and trustworthy when choosing a restaurant. What this showed me is that trust is indeed an important consideration when choosing a meal.

How Last Eats Combats Choice Paralysis

By constraining choice to the single most important/favorite meal in a given city (your current obsession, if you will), Last Eats enables you and the community at large to benefit from passionate recommendations of only the best experiences sourced from the people you trust the most. In this way, we are cutting through the clutter and endless options that hinder our competitors. Through radical selectivity, Last Eats operates at a level of focus that casual review sites lack.

We're personalizing the content by structuring the submissions around why it’s special to a user and what specifically a user recommends about it.

Finally, we're making the content vivid by allowing our users to select a tantalizing photo of their ideal meal tagged at the restaurant of their choice from Instagram.

Media Awareness of Choice Paralysis with Dining

New York Times tech writer Farhad Manjoo discussing the importance of selective recommendations

Strategy and Implementation

As a UX/UI designer, my aim was for Last Eats to be the simplest, most useful, user-centered food discovery tool on the market. Our model of radical selectivity - one restaurant, one meal, one recommendation at a time, came about as a result of my desire to completely alter the signal to noise ratio with food discovery apps. By optimizing the experience for local, personalized, actionable recommendations tailored to you, I felt we could dramatically increase the signal to noise ratio.

Gone are the average experiences, the reactionary reviews and the anonymity. Gone are the 50,000 options where everything is "great" but really isn't. I wanted to build a community of excellence, passion and love for great food and great culinary experiences with as little friction and as few pain points as possible.

Although forcing a user to articulate their one go to restaurant or obsession is challenging, I saw it as an incredibly interesting way for users to showcase their current obsessions and preferences. An intended byproduct of this approach is a community showcase of individual values, cultural connections and overall priorities. Despite its utilitarian roots, Last Eats was intended to be a part storytelling platform. Here's my current obsession, here's why I love it and here's why I made it my choice.

My Thesis Defense at ITP - NYU (on May 13th, 2014)

The Last Eats MVP

I designed a mobile optimized website that would serve as a lightweight vehicle for the core idea of Last Eats - fewer, better, more selective recommendations from friends is more useful than more options from strangers.

Technical Requirements for Production

The two-fold core requirements of the app:

Contribute Content

Browse Content

In order to do these tasks, I knew I would need to leverage a variety of social APIs.

Heroku (Platform as a service (PaaS)) - to develop, run and manage our web app

I began by hardcoding/hacking together a few simple example pages together using HTML/CSS and JQuery Mobile. I leveraged a very simple backend made with Python and MongoDB. Once the backend needs of the web app became complex enough, I hired a backend developer to serve as our data specialist. He also helped orchestrate much of the asynchronous Javascript that was required by our APIs on the front end.

1st Version of Mobile Site (May 2014)

The first version Last Eats that was built for my thesis defense was very much a minimum viable product. A user could log in through Facebook, make a single recommendation per city, see their friends entries and get directions to a restaurant based on their location. Nothing more than the essentials of what we required to launch.

User Feedback - First 50 Users

What we heard from our first 50 users was that we were missing some crucial data.

There was no indication in the newsfeed as to how close the closest restaurants were. Although the top result may be a quarter mile away, it could be 5 miles away (especially in more spread out cities). There was no way to know. As a result, this distance needed to be defined and showcased with each venue.

We also lacked some of the basic (yet now ubiquitous) labels that help a user to predict the kind of experience a venue provides. We needed to add a few basic tags for each restaurant in order to help classify the price point, the type of meal and some basic characteristics of the vibe.

Additionally, we needed a way for users to engage with the content in a more intuitive way. Our core demographic of users (18 - 40 years old) kept bringing up Instagram as a point of reference. The buttons, the clarity and the easy commenting / liking and messaging were standard parts of their digital lives. As a result, there was a push for this kind of functionality to be simply and clearly introduced to our platform - commenting, liking and saving were next to come. Most importantly, they wanted to be able to post a photo from their own meal directly onto Last Eats.

2nd Version of Site (Mobile - July 2014)

The next update to Last Eats attempted to address the most pressing user concerns and issues mentioned above. Below are screenshots that reflect some of these updates.

As an example, my friend Ian was blown away by the food and the service at Union Square Cafe and wanted to immediately update his New York Last Eats entry with this experience. This time, when he updated his Last Eats for NYC, he provided a photo that he took to represent the quality of the meal and why it was so great.

3rd Version of Site (Mobile Landing Page and Desktop Updates - August 2014)

As a mobile optimized web app, I needed Last Eats to be an easy, intuitive, superior way to discover great food on the go. The landing page for the site has a clear explanation of our purpose, a call to action to login, a button that activates an expanded "How it Works" section, recent declarations from friends and passionate eaters, and a direct way to quickly add an eat for your location.

See the annotated pages for discovering new content below

What Didn't Work

As with a Tweet or a Facebook post/status, Last Eats declarations were intended to be updated with regularity - thus allowing for a fresh feed of what is currently fueling the culinary tastes within your community. Unfortunately, this didn't happen as planned. For the most part, users created recommendations, posted them and them never changed them. The focus on a single recommendation for a single city was implemented so that the second a user added a new entry, that recommendation would supersede everything that came before it - yet keep an archive of the previous Last Eats made. This was never the natural behavior of the user. Too many people assumed their eats were etched in stone and that they couldn't alter or tweak them.

Another huge problem was that we didn't focus on a specific region to launch the platform. Although the project was inspired by and based on the New York City dining experience, we let the floodgates open to begin. From the date of my Thesis defense to the end of the summer, we accumulated nearly 500 recommendations with over 10,000 page views. Yet the recommendations were so smattered with such breadth that it was hard to reliably use the platform outside of a few cities.

The Evolution of Last Eats - September 2014

Another issue we had was the time it took to add a recommendation was too long. We had too many single page steps that required too much of the user and not enough reliance upon existing, easily found data to supplement the user generated content.

Based on this feedback, in September of 2014 I designed an easier, simpler and more intuitive content creation prototype that emphasized discovering unique culinary experiences - the content that you can't reliably source from Yelp - in a single page.

See a screenshot from this secondary site below.

This led to a more pronounced emphasis upon mood, location and experience and a lot of new questions.

Where Can We Take This?

One of the things we learned from our first users was how important it was to differentiate ourselves based on the data that users can't already source from Yelp or so many other food discovery apps. With this in mind, and our clear sense of mood and experience being an exciting focus, I began to look into what it would take to move forward with this project - shifting from an academic exercise to a socially optimized food discovery business.

Before moving forward, we needed to return to our core users and confirm with them again that we were heading in the right direction.

More User Research - September 2014

Below are a selective highlights from our users:

What is the most useful thing that Last Eats provides you as a user?

"Recommendations from people I trust ".... "its not a rating system like yelp or spponwhatvever" ...."Less clutter! Don't have to sort through tons of suggestions.".... "Recommendations from people whose taste I actually know".... "The visual content of the food is rich and high quality. Just like airbnb they are a medium for people to fantasize about what they searching for next. Last Eats should make me see a picture that someone has posted and should make me crave that food for the future. "

What is the most frustrating thing about the current Last Eats experience?

"Doesn't work on Chrome, or isnt its own app. Makes it a bit harder to navigate.".... "Not enough friends on it.".... "Adding a Last Eats in the same city replaces my existing post. I think it'd be great if each person were allowed to post their top 5 or top 10. Or perhaps it could be organized into Last Eats by neighborhood within a city. I have a few chef friends in SF and I'd love to be able to browse all of their top favorite restaurants in in the city."

What specifically would bring you back to the site more frequently?

"If I could rely on finding a great restaurant within 10 blocks of my current location, that was open during the time I searched. ".... "More details in recommendations.".... "It should be the airbnb of food. Sometime's I go on airbnb just because I'm curious where I could go and stay in some random ass country ha. That would be cool if I could go on Last Eats and have a similar feeling be evoked by what food photos are aggregated on my feed.".... "if you could become part of "friend" groups so you can only browse recommendations of people you know."

These samples of user responses seemed to give us the confidence that many of our core objectives were being validated. We are creating trusted recommendations in a streamlined, engaging manner. Like so many young platforms, we heard form our users that they wished the community was larger and that it was an app more than a website. We asked one of our test groups over the summer about the importance of presenting these recommendations in an app format and what implications that would have on engagement. What we heard was rather unequivocal.

Of our test users, 80% said that they would use Last Eats more if it were an app as opposed to a website.

Even more striking, In 2014, the percentage of time spent on mobile apps as opposed to mobile optimized web sites was 86% for apps and 14% for the web. That's a staggering contrast. If we we're going to move forward, we decided to do so as a native app.

Toast

After taking into account all of our user feedback, the sustained appetite for the more mood/experience/location based version of Last Eats, we decided to break from our earlier platform and create something new.

Enter "Toast."

Like it's predecessor, Toast is a word of mouth recommendation platform, but with some distinct differences.

It's a native iOS app

Mood and location are the foundation of the platform

You can add as many Toasts or recommendations as you want. There is no limit, but you can designate a current favorite or "Top Toast"

Restaurant reservations are enabled

We're launching in NYC only (with a focus on everything south of Union Square as well as Williamsburg)

How We See Ourselves in the Market:- We’re taking the social curation of Jelly, the intimacy and clarity of Medium with the actionable utility of Hotel Tonight. We’re humanizing the discovery process and elevating/dignifying the recommendation in a way other platforms aren’t. Additionally, with the added emphasis upon mood we see Toast as a socially sourced Stumbleupon for restaurants.